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All Journal Jurnal Ilmiah KOMPUTASI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of Information System, Applied, Management, Accounting and Research Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Indonesian Journal of Business Intelligence (IJUBI) bit-Tech Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JISA (Jurnal Informatika dan Sains) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Ilmiah Wahana Pendidikan Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science Formosa Journal of Computer and Information Science Jurnal Lentera Pengabdian International Journal of Applied Research and Sustainable Sciences (IJARSS) International Journal of Sustainable Applied Sciences (IJSAS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian JPM MOCCI : Jurnal Pengabdian Masyarakat Ekonomi, Sosial Sains dan Sosial Humaniora, Koperasi, dan Kewirausahaan SAINTEK International Journal of Integrated Science and Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi Welfare: Jurnal Pengabdian Masyarakat
Wahyu Hadikristanto
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : International Journal Software Engineering and Computer Science (IJSECS)

 1 
Grouping Production Goods Requirements Using the K-Means Clustering Method Setiawan, Dani Yuda Dwi; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2863

Abstract

The inventory management of production goods presents several challenges, including difficulties in distinguishing between necessary and unnecessary items, leading to overstocking and manual data processing issues. Additionally, the risk of data loss can impede the data processing workflow. Data testing is conducted to evaluate the accuracy of calculations and the functionality of the applied methods. The objective is to optimize production results and inventory levels in warehouses. The K-means algorithm, known for its simplicity and effectiveness, is utilized to identify clusters within the data. The first cluster (C0) has centroids at (60.33, 70.33) and includes stock data categorized as having no potential. This cluster comprises 35 records. The second cluster (C1) has centroids at (10.94, 7.11) and includes stock data categorized as available, consisting of 15 records. Testing with the RapidMiner Studio application confirms similar insights, with each cluster containing members that are divided into two clusters, each having optimal centroid values of (60.33, 70.33) for Cluster 1 (C0) and (10.94, 7.14) for Cluster 2 (C1), and a Davies-Bouldin Index evaluation score of 0.666.
Estimating Distributor Demand for Fishing Gear Products Using Linear Regression Algorithm Keswanto; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2864

Abstract

Fishing equipment plays a critical role in both recreational and commercial fishing activities across various aquatic environments. The challenge of managing inventory effectively is heightened by the fluctuating demand and the need to avoid overstocking, which can result in increased operational costs. To address this, a linear regression algorithm is utilized to predict demand for fishing products, using relevant independent variables to model the relationship with dependent variables such as monthly sales figures. This predictive model aims to provide actionable insights that can assist businesses in making informed decisions regarding inventory management and distribution strategies. The study employs the RapidMiner Studio application to develop and evaluate the model's performance, with the analysis yielding a Root Mean Square Error (RMSE) of 140.200. This relatively low RMSE value demonstrates the model's accuracy and effectiveness in forecasting demand, suggesting that the algorithm can be a valuable tool for optimizing inventory levels and ensuring product availability while minimizing excess stock.
Predicting Consumer Demand Based on Retail Stock Using the K-Nearest Neighbors Algorithm Putri N.A, Anindya; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2865

Abstract

Inefficient stock management, such as improper stock management, will result in excess or shortage of goods. Excess stock can cause high storage costs and the risk of unsold goods. Predict consumer needs based on stock. Analyze inefficient stock to improve shortages. One effective method for making this prediction is using the K-Nearest Neighbors (K-NN) algorithm. The K-NN algorithm is a simple but powerful machine-learning technique that can be used for classification and regression. The model scenario results show 24 objects in the Low-needs group and 14 in the High-needs group. Evaluation and performance testing using the Rapid Miner tool can also produce a relevant picture of the modelled scenario. The model implemented using the K-NN algorithm has an Accuracy value of 97.50% with a Standard Deviation of +/- 750%, then a Precision value of 100%, and a Recall value of 950%. By measuring model performance with cross-validation, the resulting accuracy has a standard deviation value, which aims to see the distance between the average accuracy and the accuracy of each experiment (iteration)
Co-Authors ., Sapardi Abdul Halim Anshor Abdul Hasyim Abimanyu, Aldo Anggito Aceng Badruzzaman Achmad Firmansyah Putra Ade Muslim Agung Nugroho Ahmad Fauzi Ahmad Zy Ahmad, Asyari Ali Nurdiansyah Ananto Tri Sasongko Andika, Sophian Andri Firmansyah Anggara, Bastian Anisa Anisa Anisa Rahmawati Anshor , Abdul Halim Ariandi, Sheva Rizky Arvita Emarilis Intani Aswan S Sunge Atma, Dodit Ardi Ayu Fitriyani Badruzzaman, Aceng Dahyoung Yenuargo Dichi Setiawan Diki Febriani Dodit Ardiatma Doni, Muhamad Edi Junianto Edi Widodo Edora Edora Edora Edy Widodo Eko Budiarto Ermanto Fajar Arief Rachman Fatchan, Muhammad Fauzi Ahmad Muda Febro Herdyanto Galang Rintang Widya Pratama Gatot Tri Pranoto Gunawan, Ahmad Herol Herol Holwati Ikmal Riyan Firmansyah Imam Nasai2 Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Jamroni, A. Reza Baehaqa Jamroni Karsito Keswanto Kurniadi, Nanang Tedi Laki, Abraham Leo Contantinus Meze Listanto, Firgiawan Maulida Ramadhan Mico Giovanni Dermawan Muhamad Fatchan Muhammad Farhan Alfarizi Muhammad Fatchan Muhammad Makmun Effendi Muhammad Najamuddin Dwi Miharja Muhammad Suprayogi2 Naufal Muyassar Nawangsih, Ismasari Nita Paramita Njai Njai Nur Azizah Nurhadi Surojudin Nurul Ariffaeni Islami Oktavianto, Rainal Zulian Permana , Indra Pradini, Purnama Sakhrial Prasetyo Prayoga, Dimas Preatmi Nurastuti Purdianto Purdianto Purnama Sakhrial Pradini Purwanto Purwanto Purwanto Putri N.A, Anindya Putri Nabila Adinda Adriansyah Rahmawati, Shinta Melliana Rahmawati Rasmiati Nur Aeni Retno Purwani Setyaningrum REZEKI, FITRI Risky Bambang Sutrisna romanuddin, ahmad Rosyati Adelia S Suprapto Sandi Salvan N N Sanudin Satria Permana, Muhammad Safri Sa’ad Khairudin Hanif Setiawan, Dani Yuda Dwi Siska Wulandari, Siska Sophian Andika Suderajat, Agung Sufajar, Sufajar Sufajar, Suprapto Suhardian Suhardian Suherman Suherman Suherman Sunaryati , Titin Sunita Dasman Sya syah Apriliyani Syach, Ridwan Syariefur Rakhmat, Adrianna Taofik Safrudin Taufik Hidayat Tiani Ayu Lestari Tiara Deswara Pungkas Tri Ngudi Wiyatno Turmudi Zy, Ahmad Vidya Anis Fitri Yahya, Adiba Yahya, Adibah Yoga Religia Yusup, Diana